Biocview "PrincipalComponent"

A Functional Approach To Impute Genetically Regulated Expression

A gene-signature ranking method based on sample density in PCA space

Analysis for short time-series data

Analysis of single-cell epigenomics datasets with a Shiny App

An R package for quantitative integration and analysis of multiple omics assays from heterogeneous samples

A Package to Download, Organize and Analyze Genomic Data Commons (GDC) Data

Artificial Components Detection of Differentially Expressed Genes

Batch Effects Quality Control Software

ccImpute: an accurate and scalable consensus clustering based approach to impute dropout events in the single-cell RNA-seq data

ccImpute: an accurate and scalable consensus clustering based approach to impute dropout events in the single-cell RNA-seq data (https://doi.org/10.1186/s12859-022-04814-8)

Classes and methods for multi-omics data integration

Coordinate Covariation Analysis

Correspondence Analysis for Single Cell Data

Data preprocessing and quality control for Illumina HumanMethylation450 and MethylationEPIC BeadChip

Data preprocessing and quality control for Illumina HumanMethylation450 and MethylationEPIC BeadChip (USC version)

dgeAnalysis

Differential gene expression analysis based on the negative binomial distribution

Different methods for the integrative analysis multiple omics data

Evaluate Reduced Dimension Representations

Exploratory Analysis of ATAC-seq data

Fast Methylome-Wide Association Study Pipeline for Enrichment Platforms

GENetic EStimation and Inference in Structured samples (GENESIS): Statistical methods for analyzing genetic data from samples with population structure and/or relatedness

Genomic trajectories with heterogeneous genetic and environmental backgrounds

Genotype Conditional Association TEST

Graphical Interface for Alternative Splicing Quantification, Analysis and Visualisation

Handling Missing Individuals in Multi-Omics Data Integration

Individualized Multi-Omic Pathway Deviation Scores Using Multiple Factor Analysis

Inference of gene regulatory networks from gene expression data

Infers biological signatures from gene expression data

Integrative Pathway Analysis with Modern PCA Methodology and Gene Selection

Interactive Visualization of RNA-seq Data Using a Principal Components Approach

Interactive Workflow for Discovering Rhythmicity in Biological Data

Interpretable marker-based single-cell pseudotime using Bayesian parametric models

Interpretation of RNA-seq experiments through robust, efficient comparison to public databases

Iterative Differential Clustering for single-cell

Iterative Pruning to Capture Population Structure

Iterative Pruning to Capture Population Structure version 2

Logistic Factor Analysis for Categorical Data

Multiomic Batch effect Correction

Multiple omics data integrative clustering and gene set analysis

Multivariate analysis of microarray data using ADE4

ontological exploration of scRNA-seq of 1.3 million mouse neurons from 10x genomics

Parallel Computing Toolset for Relatedness and Principal Component Analysis of SNP Data

PathoStat Statistical Microbiome Analysis Package

PCA Analysis and Visualization for Clustering

PCA, PLS(-DA) and OPLS(-DA) for multivariate analysis and feature selection of omics data

PCAtools: Everything Principal Components Analysis

PLSDA-batch

Quality control and analysis tools for Illumina DNA methylation BeadChip

Ribosome Profiling Data Analysis: from BAM to Data Representation and Interpretation

rqt: utilities for gene-level meta-analysis

scRMD: Imputation for single cell RNA-seq data via robust matrix decomposition

Shiny graphical interface and command-line for Regularized (or Sparse) Generalized Canonical Correlation Analysis (R/SGCCA)

Simulation tool for optimal design of high-dimensional MS-based proteomics experiment

Singular Value Decomposition for Bioconductor Packages

Small-Count Analysis Methods for High-Dimensional Data

Sparse Contrastive Principal Component Analysis

The Cancer Genome Atlas Data Integration

The ClusterSignificance package provides tools to assess if class clusters in dimensionality reduced data representations have a separation different from permuted data

The removal of batch effects from datasets using a PCA and constrained optimisation based technique

Tools for data visualization

Tools for Omics Data Analysis

Unified statistal Modeling of Omics Data

Visual and interactive gene expression analysis

Visualise correlation results and test significancies of these

Visualizations of expressionSet Bioconductor object

Biocview "PrincipalComponent"

R Package Documentation

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